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--- dm:start [20/05/2024 alle 06:52 (5 mesi fa)] – [Second Semester (DM2 - Data Mining: Advanced Topics and Applications)] Riccardo Guidotti
+++ dm:start [15/10/2024 alle 14:30 (4 giorni fa)] (versione attuale) – [Exam DM1] Fosca Giannotti
@@ Linea 1: / Linea 1: @@
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+====== Data Mining A.A. 2024/25 ======
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-====== Data Mining A.A. 2023/24 ======
 ===== DM1 - Data Mining: Foundations (6 CFU) =====
@@ Linea 85: / Linea 34: @@
     * Meeting: https://calendly.com/andreafedele/
 ====== News ======
+     * **[07.09.2024]** Past years' lectures available at [[https://unipiit-my.sharepoint.com/:f:/g/personal/a_fedele7_studenti_unipi_it/EkecHQpnojVLqX0OqTlfrbMBBRMFbIJfNCw_RdFPN2276g?e=Y2uIcu|link]]
-     * **[03.05.2024]** Next lecture of DM2 will be as usual on Monday 06/05 from 9 to 11 in room C.
+     * [02.09.2024] Lectures will start on Monday 30 September 2024 at 11.00 room C1.
-     * [19.01.2024 DM2 Lectures will start on Mon 19/02, only for that lecture the time will be 14-16 instead of 9-11.
+     * [02.09.2024] Lectures will be in presence only. Registrations of the lectures of past years can be found at the bottom of this web page.
-     * [13.10.2023] To schedule meeting with the Teaching Assistant you can use: https://calendly.com/andreafedele/
+     * [02.09.2024] Project Groups [[https://docs.google.com/spreadsheets/d/1RFWIwKM5Myaehh4tHceaf3olMYm_CktGvoNOFX2Oovc/edit?usp=sharing|link]]
-     * [20.09.2023] Recordings of the lectures can be found on the web pages of the course for the years 2020/2021 and 2021/2022 (see links at the bottom of this page)
+     * [11.09.2023] MS Teams [[https://teams.microsoft.com/l/team/19%3AMMVIsw09XAOGOcd8-D8dKmNUO2hKXsFKpgkOoiFnwJM1%40thread.tacv2/conversations?groupId=3f7fd5a7-5c84-4930-92e4-0704013877f2&tenantId=c7456b31-a220-47f5-be52-473828670aa1|link]]
-     * [20.09.2023] Thursday 21 September there will be no lecture.
-     * [11.09.2023] Lectures will start on Monday 18 September 2023 at 11.00 room C1.
-     * [11.09.2023] Lectures will be in presence only. Registrations of the lectures of past years can be found at the bottom of this web page.
-     * [11.09.2023] Project Groups [[https://docs.google.com/spreadsheets/d/10R5AcqdlXsqTAxSys6zyqArvdytq4HH6Ik8Uy-NHkQ4/edit?usp=sharing|link]]
-     * [11.09.2023] MS Teams [[https://teams.microsoft.com/l/team/19%3a7uEgK_aekrBFuOsbREccAa-tfqeSwvfBemfK_lG6HA01%40thread.tacv2/conversations?groupId=84cc4fec-41fc-4208-a9d4-a02675216d22&tenantId=c7456b31-a220-47f5-be52-473828670aa1|link]]
 ====== Learning Goals ======
   * DM1
@@ Linea 122: / Linea 66: @@
 ^  Day of Week  ^  Hour  ^  Room  ^
 |  Monday  |  11:00 - 13:00  |  C1   |
-|  Wednesday  |  11:00 - 13:00  |  C1  |
+|  Tuesday  |  14:00 - 16:00  |  C1  |
 **Office hours - Ricevimento:**
   * Prof. Pedreschi
-      * Monday 16:00 - 18:00
+      * TBD
       * Online
   * Prof. Guidotti
-      * Tuesday 16:00 - 18:00 or Appointment by email
+      * Thursday 16:00 - 18:00 or Appointment by email
       * Room 363 Dept. of Computer Science or MS Teams
@@ Linea 177: / Linea 121: @@
   * Didactic Data Mining [[http://matlaspisa.isti.cnr.it:5055/Help| DDMv1]], [[https://kdd.isti.cnr.it/ddm/#/| DDMv2]]
-====== Class Calendar (2023/2024) ======
+====== Class Calendar (2024/2025) ======
 ===== First Semester (DM1 - Data Mining: Foundations) =====
 ^ ^ Day ^ Time ^ Room ^ Topic ^ Material ^ Lecturer ^
-|01.| 18.09.2023 | 11-13 |C1| Overview, Introduction | {{ :dm:00_dm1_introduction_2023_24.pdf | Intro}} | Pedreschi|
+|   | 16.09.2024 | |  | No Lecture |  |  |
-|   | 20.09.2023 | 11-13 |  | No Lecture |  |  |
+|   | 17.09.2024 | |  | No Lecture |  |  |
-|02.| 25.09.2023 | 11-13 |C1| Lab. Introduction to Python | {{ :dm:dm1_lab01_python_basics.zip | Python Basic}} | Guidotti|
+|   | 23.09.2024 | |  | No Lecture |  |  |
-|03.| 27.09.2023 | 11-13 |C1| Lab. Data Understanding | {{ :dm:dm1_lab02_data_understanding.zip | Data Understanding}} | Guidotti|
+|   | 24.09.2024 | |  | No Lecture |  |  |
-|04.| 02.10.2023 | 11-13 |C1| Data Understanding | {{ :dm:01_dm1_data_understanding_2023_24.pdf | Data Understanding}} | Guidotti|
+|01.| 30.09.2024 | 11-13 |C1| Overview, Introduction | {{ :dm:00_dm1_introduction_2024_25.pdf | Intro}} | Pedreschi|
-|05.| 04.10.2023 | 11-13 |C1| Data Understanding & Preparation | {{ :dm:01_dm1_data_understanding_2023_24.pdf | Data Understanding}}, {{ :dm:02_dm1_data_preparation_2023_24.pdf | Data Preparation}} | Pedreschi|
+|02.| 01.10.2024 | 14-16 |C1| Lab. Introduction to Python | {{ :dm:dm1_lab01_python_basics_2024_25.zip | Python Basics}} | Pedreschi|
-|06.| 09.10.2023 | 11-13 |C1| Data Preparation & Data Similarity | {{ :dm:02_dm1_data_preparation_2023_24.pdf | Data Preparation}}, {{ :dm:03_dm1_data_similarity_2023_24.pdf | Data Similarity}} | Pedreschi|
+|03.| 07.10.2024 | 11-13 |C1| Data Understanding | {{ :dm:01_dm1_data_understanding_2024_25.pdf | Data Understanding}} | Pedreschi|
-|07.| 11.10.2023 | 11-13 |C1| Data Similarity & Lab. Data Understanding | {{ :dm:03_dm1_data_similarity_2023_24.pdf | Data Similarity}}, {{ :dm:dm1_lab02_data_understanding.zip | Data Understanding}} | Pedreschi|
+|04.| 08.10.2023 | 14-16 |C1| Data Understanding & Preparation | {{ :dm:01_dm1_data_understanding_2024_25.pdf | Data Understanding}}, {{ :dm:02_dm1_data_preparation_2024_25.pdf | Data Preparation}} | Pedreschi|
-|08.| 16.10.2023 | 11-13 |C1| Introduction to Clustering, K-Means | {{ :dm:04_dm1_clustering_intro_2023_24.pdf | Intro_Clustering}}, {{:dm:05_dm1_kmeans_2023_24.pdf | K-Means }} | Pedreschi|
+|05.| 14.10.2023 | 11-13 |C1| Data Preparation & Similarity | {{ :dm:02_dm1_data_preparation_2024_25.pdf | Data Preparation}}, {{ :dm:03_dm1_data_similarity_2024_25.pdf | Data Similarity}} | Pedreschi|
-|09.| 18.10.2023 | 11-13 |C1| Clustering Validation, Hierarchical Clustering | {{ :dm:04_dm1_clustering_intro_2023_24.pdf | Intro_Clustering}}, {{ :dm:06_dm1_hierarchical_clustering_2023_24.pdf | Hierarchical}} | Pedreschi|
+|06.| 15.10.2024 | 14-16 |C1| Lab. Data Understanding | {{ :dm:dm1_lab02_data_understanding.zip | Data Understanding}}| Pedreschi|
-|10.| 23.10.2023 | 11-13 |C1| Density-based Clustering | {{ :dm:07_dm1_density_based_2023_24.pdf | Density-based Clustering}} | Pedreschi|
-|11.| 25.10.2023 | 11-13 |C1| Lab. Clustering | {{ :dm:dm1_lab03_clustering.zip | Clustering}}| Guidotti|
-|12.| 30.10.2023 | 11-13 |C1| Ex. Clustering | {{ :dm:ex1_dm1_clustering_2023_24.pdf | ExClustering}}| Guidotti|
-|   | 01.11.2023 | 11-13 |  | No Lecture |  |  |
-|13.| 06.11.2023 | 11-13 |C1| Intro Classification, kNN[[https://unipiit.sharepoint.com/sites/a__td_61280/Shared%20Documents/General/Recordings/Lecture%2006_11_2023-20231106_110052-Registrazione%20della%20riunione.mp4?web=1|(video)]] | {{ :dm:08_dm1_classification_intro_2023_24.pdf | Intro_Classification}}, {{ :dm:09_dm1_knn_2023_24.pdf | kNN}}| Guidotti|
-|14.| 08.11.2023 | 11-13 |C1| Naive Bayes, Exercises | {{ :dm:10_dm1_naive_bayes_2023_24.pdf | Naive Bayes}} | Guidotti|
-|15.| 13.11.2023 | 11-13 |C1| Model Evaluation | {{ :dm:11_dm1_classification_eval_2023_24.pdf | Model Evaluation}} | Guidotti|
-|16.| 15.11.2023 | 11-13 |C1| Model Evaluation Exercises & Lab | {{ :dm:dm1_lab04_classification_regression.zip | Classification}} | Guidotti|
-|   | 20.11.2023 | 11-13 |  | No Lecture |  |  |
-|17.| 22.11.2023 | 11-13 |C1| Decision Tree Classifier | {{ :dm:12_dm1_decision_trees_2023_24.pdf | Decision Tree}} | Pedreschi|
-|18.| 27.11.2023 | 11-13 |C1| Decision Tree Classifier | {{ :dm:12_dm1_decision_trees_2023_24.pdf | Decision Tree}} | Pedreschi|
-|19.| 29.11.2023 | 11-13 |C1| Exercises and Lab. Decision Tree Classifier | {{ :dm:dm1_lab04_classification.zip | Decision Tree}} | Guidotti|
-|20.| 04.12.2023 | 11-13 |C1| Decision Tree Classifier, Exercises and Lab | {{ :dm:12_dm1_decision_trees_2023_24.pdf | Decision Tree}} | Pedreschi|
-|21.| 06.12.2023 | 11-13 |C1| Intro Regression & Lab. Regression | {{ :dm:12_dm1_linear_regression_2023_24.pdf | Regression}}, {{ :dm:dm1_lab05_regression.zip | Regression}} | Guidotti|
-|22.| 11.12.2023 | 11-13 |C1| Into Pattern Mining and Apriori | {{ :dm:13_dm1_pattern_mining_2023_24.pdf | Pattern Mining}} | Pedreschi|
-|23.| 13.12.2023 | 16-18 |C1| Apriori & Lab. Pattern Mining | {{ :dm:13_dm1_pattern_mining_2023_24.pdf | Pattern Mining}}, {{ :dm:dm1_lab06_pattern_mining.zip | Pattern Mining}}  | Pedreschi|
-|24.| 18.12.2023 | 11-13 |C| FP-Growth and Exercises | {{ :dm:13_dm1_pattern_mining_2023_24.pdf | Pattern Mining}} | Guidotti|
 ===== Second Semester (DM2 - Data Mining: Advanced Topics and Applications) =====
 ^ ^ Day ^ Time ^ Room ^ Topic ^ Material ^ Lecturer ^
 |01.| 19.02.2024 | 14-16 |C| Overview, Rule-based Models | {{ :dm:14_dm2_intro_2023_24.pdf | Introduction}}, {{ :dm:dm2_project_guidelines_23_24.pdf | Guidelines}}, {{ :dm:15_dm2_rule_based_classifier_2023_24.pdf | Rule-based Models }} | Guidotti|
-|   | 21.02.2024 |  | | No Lecture |  |  |
-|   | 26.02.2024 |  | | No Lecture |  |  |
-|02.| 19.02.2024 | 11-13 |C| Sequential Pattern Mining | {{ :dm:16_dm2_sequential_pattern_mining_2023_24.pdf | Sequential Pattern Mining}}, {{ :dm:GSP.zip | GSP}} | Guidotti|
-|03.| 04.03.2024 | 9-11 |C| Sequential Pattern Mining | {{ :dm:16_dm2_sequential_pattern_mining_2023_24.pdf | Sequential Pattern Mining}}, {{ :dm:GSP.zip | GSP}} | Guidotti|
-|04.| 06.03.2024 | 11-13 |C| Transactional Clustering | {{ :dm:17_dm2_transactional_clustering_2023_24.pdf | Transactional Clustering}} | Guidotti|
-|05.| 11.03.2024 | 9-11 |C| Time Series Similarity | {{ :dm:18_dm2_time_series_similarity_2023_24.pdf | Time Series Similarity}}, {{ :dm:dm2_lab00_spotify.zip | TS_Load}}, {{ :dm:dm2_lab01_dist_transf.zip | TS_Similarity}} | Guidotti|
-|06.| 13.03.2024 | 11-13 |C| Time Series Approximation | {{ :dm:19_dm2_time_series_clustering_approximation_2023_24.pdf | Time Series Clustering}}, {{ :dm:dm2_lab02_approx_clust.zip | TS_Approx_Clustering}} | Guidotti|
-|07.| 18.03.2024 | 9-11 |C| Time Series Clustering & Motifs| {{ :dm:20_dm2_time_series_matrix_profile_2023_24.pdf | Time Series Motifs}}, {{ :dm:dm2_lab03_motifs.zip | TS_Motifs}} | Guidotti|
-|08.| 20.03.2024 | 11-13 |C| Time Series Classification | {{ :dm:21_dm2_time_series_classification_2023_24.pdf | Time Series Classification}}, {{ :dm:dm2_lab04_classification.zip | TS_Classification}} | Guidotti|
-|09.| 25.03.2024 | 9-11 |C| Imbalanced Learning | {{ :dm:22_dm2_imbalanced_learning_2023_24.pdf | Imbalanced Learning}}, {{ :dm:dm2_lab05_imbalance.zip |ImbLearn}} | Guidotti|
-|10.| 27.03.2024 | 11-13 |C| Dimensionality Reduction | {{ :dm:23_dm2_dimred_2023_24.pdf | Dimensionality Reduction}}, {{ :dm:dm2_lab06_dimred.zip |DimRed}} | Guidotti|
-|11.| 03.04.2024 | 11-13 |C| Outlier Detection | {{ :dm:24_dm2_anomaly_detection_2023_24.pdf | Outlier Detection}} | Guidotti|
-|12.| 08.04.2024 | 9-11 |C| Outlier Detection | {{ :dm:24_dm2_anomaly_detection_2023_24.pdf | Outlier Detection}}, {{ :dm:dm2_lab07_outlier_det.zip | OutlierDetection}} | Guidotti|
-|13.| 10.04.2024 | 11-13 |C| Outlier Detection | {{ :dm:24_dm2_anomaly_detection_2023_24.pdf | Outlier Detection}}, {{ :dm:dm2_lab07_outlier_det.zip | OutlierDetection}} | Guidotti|
-|14.| 15.04.2024 | 14-16 |C| Gradient Descend, MLE | {{ :dm:25_dm2_gradient_descent_2023_24.pdf | GD}}, {{ :dm:26_dm2_maximum_likelihood_estimation_2023_24.pdf | MLE}} | Guidotti|
-|15.| 17.04.2024 | 11-13 |C| Odds, LogOdds, Logistic Regression| {{ :dm:27_dm2_odds_2023_24.pdf | Odds}}, {{ :dm:28_dm2_logistic_regression_2023_24.pdf | LogReg}}, {{ :dm:dm2_lab08_logistic_reg.zip | LogReg}} | Guidotti|
-|16.| 22.04.2024 | 9-11 |C| Support Vector Machine | {{ :dm:29_dm2_svm_2023_24.pdf | SVM}}, {{ :dm:dm2_lab09_svm.zip | SVM}} | Guidotti|
-|17.| 24.04.2024 | 11-13 |C| Perceptron, Neural Networks| {{ :dm:30_dm2_perceptron_2023_24.pdf | Perceptron}} | Guidotti|
-|18.| 29.04.2024 | 9-11 |C| Deep Neural Networks | {{ :dm:31_dm2_neural_network_2023_24.pdf | Deep Neural Networks}}, {{ :dm:dm2_lab10_neural_networks.zip | NN}} | Guidotti|
-|19.| 06.05.2024 | 9-11 |C| CNN, RNN, DL-TS, Ensemble Intro | {{ :dm:31_dm2_neural_network_2023_24.pdf |DNN}}, {{ :dm:21_dm2_time_series_classification_2023_24.pdf | TSC-DNN}}, {{ :dm:32_dm2_ensemble_2023_24.pdf | Ensemble}} | Guidotti|
-|20.| 08.05.2024 | 11-13 |C| Ensemble, Boosting, Adaboost | {{ :dm:32_dm2_ensemble_2023_24.pdf | Ensemble}}, {{ :dm:dm2_lab11_ensamble.zip | LabEnsemble}} | Guidotti|
-|21.| 13.05.2024 | 9-11 |C| Ensemble-TS, Gradient Boosting | {{ :dm:33_dm2_gradient_boost_2023_24.pdf | Gradient Boosting Machines}}, {{ :dm:dm2_lab11_ensamble.zip | LabEnsemble}}  | Guidotti|
-|22.| 15.05.2024 | 11-13 |C| Extreme Gradient Boosting | {{ :dm:33_dm2_gradient_boost_2023_24.pdf | Gradient Boosting Machines}}, {{ :dm:dm2_lab11_ensamble.zip | LabEnsemble}} | Guidotti|
-|23.| 20.05.2024 | 9-11 |C1| eXplainable Artificial Intelligence | {{ :dm:34_dm2_explainability_2023_24.pdf | XAI}}, {{ :dm:dm2_lab12_xai.zip | LabXAI}} | Guidotti|
-|24.| 22.05.2024 | 11-13 |C1| eXplainable Artificial Intelligence | {{ :dm:34_dm2_explainability_2023_24.pdf | XAI}}, {{ :dm:dm2_lab12_xai.zip | LabXAI}}  | Guidotti|
 ====== Exams ======
@@ Linea 264: / Linea 170: @@
 ===== Exam Booking Periods =====
   * Exam portal link: [[https://esami.unipi.it/|here]]
-  * 1st Appello: from 09/01/2024 to 31/12/2024
+  * 1st Appello: from TBD to TBD
-  * 2nd Appello: from 01/02/2024 to 17/02/2024
+  * 2nd Appello: from TBD to TBD
-  * 3rd Appello: from 05/05/2024 to 30/05/2024
+  * 3rd Appello: from TBD to TBD
-  * 4th Appello: from 02/06/2024 to 27/06/2024
+  * 4th Appello: from TBD to TBD
-  * 5th Appello: from 19/06/2024 to 14/07/2024
+  * 5th Appello: from TBD to TBD
-  * 6th Appello:
+  * 6th Appello: from TBD to TBD
 ===== Exam Booking Agenda =====
-  * 1st Appello - DM1: https://agende.unipi.it/yra-ief-dmo, DM2: https://agende.unipi.it/rnm-urj-wsu
+When registering for the oral exam please specify in the notes DM1 if you do not want to do DM2 (that is assumed by default). After having booked for DM1 please contact Prof. Pedreschi to agree on the exam date (put Prof. Guidotti and Andrea Fedele in cc). There will be no agenda for DM1.
-  * 2nd Appello - DM1: https://agende.unipi.it/yra-ief-dmo, DM2: https://agende.unipi.it/rnm-urj-wsu
-  * 3rd Appello: - DM1 & DM2: from 04/06/2024 to 07/06/2024 (deliver project by 29/05/2024)
+  * 1st Appello - DM1 & DM2: from TBD to TBD (deliver project by TBD)
-  * 4th Appello: - DM1 & DM2: from 02/07/2024 to 05/07/2024 (deliver project by 25/06/2024)
+  * 2nd Appello - DM1 & DM2: from TBD to TBD (deliver project by TBD)
-  * 5th Appello: - DM1 & DM2: from 19/07/2024 to 24/07/2024 (deliver project by 12/06/2024)
+  * 3rd Appello: - DM1 & DM2: from TBD to TBD (deliver project by TBD)
-  * 6th Appello:
+  * 4th Appello: - DM1 & DM2: from TBD to TBD (deliver project by TBD)
+  * 5th Appello: - DM1 & DM2: from TBD to TBD (deliver project by TBD)
+  * 6th Appello: - DM1 & DM2: from TBD to TBD (deliver project by TBD)
 **Do not forget to make the evaluation of the course!!!**
@@ Linea 286: / Linea 195: @@
   * An **oral exam**, that includes: (1) discussing the project report; (2) discussing topics presented during the classes, including the theory and practical exercises.
-  * A **project**, that consists in exercises requiring the use of data mining tools for analysis of data. Exercises include: data understanding, clustering analysis, pattern mining, and classification (guidelines will be provided for more details). The project has to be performed by min 2, max 3 people. It has to be performed by using Python or any other data mining software. The results of the different tasks must be reported in a unique paper. The total length of this paper must be max 20 pages of text including figures. The paper must be emailed to [[andrea.fedele@phd.unipi.it]] and [[riccardo.guidotti@unipi.it]]. Please, use “[DM1 2023-2024] Project” in the subject.
+  * A **project**, that consists in exercises requiring the use of data mining tools for analysis of data. Exercises include: data understanding, clustering analysis, pattern mining, and classification (guidelines will be provided for more details). The project has to be performed by min 2, max 3 people. It has to be performed by using Python or any other data mining software. The results of the different tasks must be reported in a unique paper. The total length of this paper must be max 20 pages of text including figures. The paper must be emailed to [[andrea.fedele@phd.unipi.it]] and [[riccardo.guidotti@unipi.it]]. Please, use “[DM1 2024-2025] Project” in the subject.
   * **Dataset**
-    - Assigned: 25/09/2023
+    - Assigned: 15/10/2024
-    - MidTerm Submission: 15/11/2023 (+0.5) (half project required, i.e., Data Understanding & Preparation and Clustering)
+    - MidTerm Submission: 15/11/2024 (+0.5) (half project required, i.e., Data Understanding & Preparation and Clustering)
-    - Final Submission: 31/12/2023 (+0.5) one week before the oral exam (complete project required).
+    - Final Submission: 31/12/2024 (+0.5) one week before the oral exam (complete project required).
-    - Dataset: {{ :dm:std.zip | STD}}
+    - Dataset: {{ :dm:dm1_dataset_2425_imdb.zip | IMDb}}
 ** DM1 Project Guidelines **
-See {{ :dm:dm1_project_guidelines_23_24.pdf | Project Guidelines}}.
+See {{ :dm:dm1_project_guidelines_24_25.pdf | Project Guidelines}}.
@@ Linea 310: / Linea 219: @@
   * **Dataset**
-    - Assigned: 19/02/2024
+    - Assigned: TBD
     - MidTerm Submission: 07/05/2024 (Modules 1 and 2 (for TS classification non DL-based models))
     - Final Submission: one week before the oral exam (complete project required, also with DL-based models for TS classification).
-    - Dataset: [[https://unipiit-my.sharepoint.com/:u:/g/personal/a_fedele7_studenti_unipi_it/EUSyNv8ahD9FrBZ6fiF3gvABcYVLpbo1biIyOGy8AmcO5g?e=ziQtEc|STD]]
+    - Dataset: TBD
 ** DM2 Project Guidelines **
@@ Linea 341: / Linea 250: @@
 ====== Previous years =====
+  * [[dm_ds2023-24]]
   * [[dm.2022-23ds]]
   * [[dm.2021-22ds]]